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Self-Adaptive systems are expected to adapt to unanticipated run-time events using imperfect information about their environment. This entails handling the effects of uncertainties in decision-making, which are not always considered as a first-class concern. This technical report summarizes a set of existing techniques and insights into addressing uncertainty in self-adaptive systems and outlines a future research agenda on uncertainty management in self-adaptive systems. The material in this report is strongly informed by our own research in the area, and is therefore not necessarily representative of other works.

@TechReport{Camara/UncertaintyTR/2017,
AUTHOR = {C\'{a}mara, Javier and Garlan, David and Kang, Won Gu and Peng, Wenxin and Schmerl, Bradley},
TITLE = {Uncertainty in Self-Adaptive Systems},
YEAR = {2017},
MONTH = {July},
NUMBER = {CMU-ISR-17-110},
INSTITUTION = {Institute for Software Research, Carnegie Mellon University},
PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/CMU-ISR-17-110.pdf},
ABSTRACT = {Self-Adaptive systems are expected to adapt to unanticipated run-time events using imperfect information about their environment. This entails handling the effects of uncertainties in decision-making, which are not always considered as a first-class concern. This technical report summarizes a set of existing techniques and insights into addressing uncertainty in self-adaptive systems and outlines a future research agenda on uncertainty management in self-adaptive systems. The material in this report is strongly informed by our own research in the area, and is therefore not necessarily representative of other works.},
NOTE = {http://reports-archive.adm.cs.cmu.edu/anon/isr2017/abstracts/17-110.html},
KEYWORDS = {Human-in-the-loop, Self-adaptation, uncertainty}
}